" Co-creating and collective intelligence/wisdom are forming a hybrid forces, a calling to reclaim the participation of people in groups as positive, useful, healing, life affirming. We alter the way that we see the world in order to solve problems together.It is a fact that humans today love to participate in problem-solving online, to have a voice and to express themselves, to be a part of the story-telling of new media, and to be a part of the collective intelligence process. The cultural, economic and political changes brought on by online intelligence sharing, via different media, have been truly amazing and reflect extraordinary cultural shifts in the 21st century. There is a huge opportunity out of there, people feel right to collaborate to solve higher issues, higher order of problems or matters."

"A new NBER working paper suggests it’ll be those that require strong social skills — which it defines as the ability to work with others — something that has proven to be much more difficult to automate. “The Growing Importance of Social Skills in the Labor Market,” shows that nearly all job growth since 1980 has been in occupations that are relatively social skill-intensive — and it argues that high-skilled, hard-to-automate jobs will increasingly demand social adeptness."

Howard Rheingold's insight:

Working with people, using technology, becomes increasingly important as artificial intelligence and intelligence augmentation tools grow more capable. This includes noncognitive skills and more skills that fall into the area of emotional intelligence.

The two aspects of being human that set us apart from other mammals are metacognition and the deep desire to belong or feel felt. Our sense of needing to belong to a group is an inherited part of our neurobiology, and collaboration with others is the desired outcome. Metacognition is our brains' miraculous innate ability to self-assess, think about our thinking, and reshape our perspectives.

Feeling the emotions of others, social acceptance, and cooperation are critical to our early development of the identity and industry stages. Author and motivational speaker Daniel Pink states that the future belongs to conceptual cooperative thinkers.

Howard Rheingold's insight:

Wonderfully, this post addresses three subjects I track because I know they are important: metacognition and its role in infotention, augmented collective intelligence, and the relationship of human cooperation to social media.

The IBM computer Deep Blue’s 1997 defeat of world champion Garry Kasparov is one of the most famous events in chess history. But Kasparov himself and some computer scientists believe a more significant result occurred in 2005—and that it should guide how we use technology to make decisions and get work done.

In an unusual online tournament, two U.S. amateurs armed with three PCs snatched a $20,000 prize from a field of supercomputers and grandmasters. The victors’ technology and chess skills were plainly inferior. But they had devised a way of working that created a greater combined intelligence—one in which humans provided insight and intuition, and computers brute-force predictions.

Howard Rheingold's insight:

A lot of talk about AI these days, and not so much talk about augmentation -- collective intelligence amplified by machine intelligence. Palantir is mostly known for its connections to intelligence agencies, but does touch base with Licklider's original (1960!) notion of "Human-Computer Symbiosis").

Collective intelligence has existed at least as long as humans have, because families, armies, countries, and companies have all--at least sometimes--acted collectively in ways that seem intelligent. But in the last decade or so a new kind of collective intelligence has emerged: groups of people and computers, connected by the Internet, collectively doing intelligent things. In order to understand the possibilities and constraints of these new kinds of intelligence, a new interdisciplinary field is emerging.

This book will introduce readers to many disciplinary perspectives on behavior that is bothcollective and intelligent. By collective, we mean groups of individual actors, including, for example, people, computational agents, and organizations. By intelligent, we mean that the collective behavior of the group exhibits characteristics such as, for example, perception, learning, judgment, or problem solving."

"Collective intelligence" is a phrase that is much used these days. I can think of no more authoritative and useful center of i nquiry than the Center for Collective Intelligence set up by Tom Malone at MIT. I'm looking forward to this one.

This book will introduce readers to many disciplinary perspectives on behavior that is bothcollective and intelligent. The goal of this edited volume is to help catalyze research in the field of collective intelligence by laying out a shared set of research challenges and methodological perspectives.

"This book will introduce readers to many disciplinary perspectives on behavior that is both collective and intelligent. By collective, we mean groups of individual actors, including, for example, people, computational agents, and organizations. By intelligent, we mean that the collective behavior of the group exhibits characteristics such as, for example, perception, learning, judgment, or problem solving. "

This article is an extremely good look into what the modern day era has created in terms of collective intelligence. The article comes from an extremely credible source, and is an extensive and comprehensive study into the topic. I\Of all the articles i have found, this is the one I would recommend to someone who wanted to gain a better understanding on the topic.

Alex Pentland says data, sensors and smartphones are opening the door to what he calls “social physics.” It is the subject of his new book, about the implications of being able to monitor and measure the flow of ideas in companies, markets and communities as never before. The payoff, he says, should be the acceleration of the pace of innovation.

Howard Rheingold's insight:

I've visited Pentland's lab and have interviewed him. He knows what he's doing, and his work always has both an empirical basis and positive social impact in mind. The connection might be tangential, but I feel there is a connection between the Social Physics that Pentland writes about and the "soft" knowledge needed to understand and effectively manage augmented collective intelligence.

"As the regular General Assemblies are where all constituents gather to listen and contribute to the discussions using the methodology of the ‘stack’, which allows anyone seeking to propose a group or report on current activities, joins a queue and takes their turn to speak. This allows each their turn to vocalise and articulate for all to hear and vote on. In a ‘leaderless’ holarchic society, the necessity for a self organising infrastructure to support the intrinsic momentum, and the forum to voice the fomenting processes of each, are both vital components. What is being revealed here is the desire for a new manner of building community, responsive to those who have been inspired to collaborate, as working groups become the lifeblood of the movement."

The insect image is misleading. Augmented collective intelligence, from the emergence of speech to the invention of writing, printing, networked computation, is about the uniquely human ability to make individual decisions in harmony with cultural norms: we invent ways to communicate work-arounds to our individual self-interest, enlisting others in collective action through norms, reputation, punishment, ideology, persuasion. The General Assembly is a cultural experiment in such a workaround for groups of mostly strangers to manage a non-hierarchical, spontaneous, vehicle for the public sphere.

"IFTTT can be combined with Evernote to make a powerful collaborative research tool, because it allows you to combine the collaboration and cloud-access of Evernote with the easy access to information offered by RSS feeds. Here’s an example:

My public forum debate team is researching the Middle East for debates in November. The Council on Foreign Relations runs a blog called “Middle East Matters,” which you can subscribe to via RSS. So first I created an Evernote folder call “Middle East Matters,” then shared it with all the members of the team. Then I created a recipe so that every time a new item is pushed out by the “Middle East Matters” RSS feed, IFTTT creates a new note in Evernote out of that item. Voilà! I have now effortlessly shared the latest updates from the Middle East with my PF team."

Howard Rheingold's insight:

IFTTT ---> Evernote can be a powerful addition to the toolset for a group who research or track topics together (as is Diigo groups). With my students, we experiment with a lot of tools, then collaborative teams can decide on their own whether to use wikis or Google Docs, Twitter hashtags, Scoop.it, G+ Hangouts, on their project.

"Real network models are new modes, not modifications of the old ones, and cooperation is how work gets done. Some examples:

Wirearchy: a dynamic multi-way flow of power and authority based on information, knowledge, trust and credibility, enabled by interconnected people and technology.

Heterarchies are networks of elements in which each element shares the same “horizontal” position of power and authority, each playing a theoretically equal role [wikipedia].

Chaordic refers to a system of governance that blends characteristics of chaos and order. The term was coined by Dee Hock the founder and former CEO of the VISA credit card association [wikipedia]."

Howard Rheingold's insight:

Once again, Harold Jarche sees deeply into the intersection of human thought, network dynamics, and the power of augmentation by digital media. The use of powerful individual media, from smartphones to laptops to wearables, and global digital networks is only part of the picture of augmented collective intelligence. Understanding the different forms of collective action, their motivations and limitations, is key. Understanding the differences between cooperation and collaboration, hierarchies and heterarchies, for example.

"Goteo is a social network for crowdfunding and distributed collaboration (services, infrastructures, microtasks and other resources) for encouraging the independent development of creative and innovative initiatives that contribute to the common good, free knowledge, and open code.

A platform for investing in "feeder capital" that supports projects with social, cultural, scientific, educational, technological, or ecological objectives that generate new opportunities for the improvement of society and the enrichment of community goods and resources."

Howard Rheingold's insight:

Crowdfunding is a form of augmented collective intelligence that enables those who share an interest in a particular kind of development to invest in manifesting it. But Goteo seems worthy of this more selective collection of resources because of its goal of stimulating progress in social and economic goods that aren't provided by markets alone. Goteo originated in Spain.

"When researchers look at the aspects of meaning that matter for grammar across different languages, many of the same aspects pop up over and over again. Does the verb describe something changing (break vs. hit)? Does it describe something only people can do (own, know, believe vs. exist, break, roll)? Does it describe an event or a state (frighten vs. fear)? This is too suspicious of a pattern to be accidental. Researchers like Steven Pinker have argued that language cares about these aspects of meaning because these are basic distinctions our brain makes when we think and reason about the world (see Stuff of Thought). Thus, the structure of language gives us insight into the structure of thought"

Howard Rheingold's insight:

One problem with testing the relationships between grammar, meaning, and thought is the difficulty of checking every verb in every grammatical construction for every aspect of meaning would be intractable for individuals or entire institutions. That's where VerbCorner comes in, a platform for testing questions about verbs. Between May and Octobe, 2013, 641 verbs and six different aspects of meaning had been examined by 1513 volunteers who provided 117, 584 judgements -- enough data to begin analyzing. Citizen science is entering the study of the mind. It won't be long before forms of augmented collective intelligence explore the possibility spaces around augmented collective intelligence: Now that we know how to use networks to enable strangers to solve problems together, we can use the methods that emerge to build better platforms -- Doug Engelbart called this "bootstrapping," and it's the driving force of augmented collective intelligence.

"Humans obviously evolved a much wider range of communication tools to express their thoughts, the most important being language," said John Hoffecker, a fellow at the University of Colorado's Institute of Arctic and Alpine Research. "Individual human brains within social groups became integrated into a neurologic Internet of sorts, giving birth to the mind."

There is abundant fossil and archaeological evidence for the evolution of the human mind, including its unique power to create a potentially infinite variety of thoughts expressed in the form of sentences, art and technologies," according to Hoffecker. "He attributes the evolving power of the mind to the formation of what he calls the "super-brain," or collective mind, an event that took place in Africa no later than 75,000 years ago."

Howard Rheingold's insight:

Augmented collective intelligence must have started with the emergence of language in Homo Sapiens, which appears to have happened relatively recently in evolutionary time (i.e., humans were a distinct species for at least a hundred thousand years before language probably emerged). As Robert K. Logan and others have asserted, language and conceptual thought probably co-evolved, providing affordances for each other. And with language came culture -- the collection of methods, practices, customs, rituals, knowledge that makes it possible for individual insight and discovery to spread throughout groups.

Augmented collective intelligence depends on technological amplification of the ability of humans to think, communicate, and work together -- and upon the norms, methods, and institutions that humans create to overcome social dilemmas. Wikipedia's Neutral Point of View is a perfect example of this kind of techno-social arrangement.

We examine whether collective intelligence helps achieve a neutral point of view (NPOV) using data from Wikipedia’s articles on US politics. Our null hypothesis builds on Linus’ Law, often expressed as “Given enough eyeballs, all bugs are shallow.” Our findings are consistent with a narrow interpretation of Linus’ Law, namely, a greater number of contributors to an article makes an article more neutral. No evidence supports a broad interpretation of Linus’ Law. Moreover, several empirical facts suggest the law does not shape many articles. The majority of articles receive little attention, and most articles change only mildly from their initial slant. Our study provides the first empirical evidence on the limit of collective intelligence. While many managers believe that they could improve their products by taking advantage of the wisdom of crowds, we show that in the case of Wikipedia, there are aspects such as NPOV that collective intelligence does not help achieve successfully.

"Three subfields of application of computational intelligence technologies to support various forms of collective intelligence are of special attention but are not the only ones: semantic web (as an advanced tool increasing collective intelligence), social network analysis (as the field targeted to the emergence of new forms of CCI), and multiagent systems (as a computational and modeling paradigm especially tailored to capture the nature of CCI emergence in populations of autonomous individuals)."

Interesting combination of computational and social approaches to augmented ("computational") collective intelligence -- this conference is an indicator that serious collective intelligence research is maturing.

3. Modern hunter-gatherers are ever vigilant against free-riding and elite-exploitation (both as dangerous to team survival as any predator). They rigidly enforce social rules to ensure skilled cooperators fare better than self-maximizers. For example: Another stakeholder distributes meat, not whoever made the kill. Rule-enforcement techniques = ridicule, shaming, shunning, and, ultimately, exile or execution.

Howard Rheingold's insight:

Cooperation sounds nice, but it needs to be enforced through norms and sanctions -- an institution for collective action that uses moral agreements (rules and norms) to overcome social dilemmas (self-interest versus joining mutually beneficial collective action)

What if we were to reframe the situation? What if, rather than asking the traditional question—What tasks currently performed by humans will soon be done more cheaply and rapidly by machines?—we ask a new one: What new feats might people achieve if they had better thinking machines to assist them? Instead of seeing work as a zero-sum game with machines taking an ever greater share, we might see growing possibilities for employment. We could reframe the threat of automation as an opportunity for augmentation.

The two of us have been looking at cases in which knowledge workers collaborate with machines to do things that neither could do well on their own. And as automation makes greater incursions into their workplaces, these people respond with a surprisingly broad repertoire of moves. Conventional wisdom is that as machines threaten their livelihood, humans must invest in ever higher levels of formal education to keep ahead. In truth, as we will discuss below, smart people are taking five approaches to making their peace with smart machines.

Howard Rheingold's insight:

To further reframe: What might people be able to do together, augmented by machines, that we are not able to do (or find it too onerous or expensive to do) without artificial augmentation?

Recent experience with government-convened hackathons has generated insights into the methods and instruments used to design effective mass collaboration efforts.

Howard Rheingold's insight:

The application of mass collaboration to social problems has been explored through Hackathons. This brief, multi-author article from Stanford Social Innovation Review offers insights from government-sponsored hackathons in which a variety of private sphere organizations and individuals contributed,

"The human species can be defined by its special ability to manipulate symbols. Each great augmentation in this ability has brought enormous economic, social, political, religious, epistemological, educational (and so on) changes.

I think that there has been only 4 of these big changes. The first one is related to the invention of writing, when symbols became permanent and reified. The second one corresponds to the invention of the alphabet, indian numerals and other small groups of symbols able to represent “almost everything” by combination. The third one is the invention of the printing press and the subsequent invention of electronic mass media. In this case, the symbols were reproduced and transmitted by industrial machines. We are currently at the beginning of a fourth big anthropological change, because the symbols can now be transformedby massively distributed automata in the digital realm. My main hypothesis is that we still did not have invented the symbolic systems and cultural institutions fitting the new algorithmic medium. "

Howard Rheingold's insight:

Pierre Levy has been thinking deeply about augmented collective intelligence for a long time and has written extensively. In this blog post, he succinctly summarizes his research into what he calls "Information Economy MetaLanguage."

Spurned by universities, a scientist plans to raise $1.5 million through online solicitations to try to find treatments for rare metabolic disorders.

Howard Rheingold's insight:

What tingled my collective intelligence antennae about this crowdfunding story is the hybrid of scientific research -- the use of technical equipment and well-described public experimentation -- and crowdfunding. In the olden days, scientists were usually aristocrats, or they depended on wealthy patrons. The university-defense-health-industry complex have constituted multiple but still very small numbers of gatekeepers for government and corporate research dollars. I don't think we know what lies down this road. Will populist funding of knowledge discovery be a healthier mechanism than NSF, DOD & Monstanto?

"FOLDIT IS PART of a growing trend toward citizen science: enabling ordinary people, often without formal training, to contribute to scientific research in their spare time. The range of involvement varies. Some citizen scientists donate idle time on their home computers for use in solving problems large in scale (the search for intergalactic objects, as in Einstein@home) or small (folding proteins). Other projects encourage participants to contribute small bits of data about themselves or their environments. The Great Sunflower Project, for instance, provides a platform for logging and sharing observations of pollinators like bees and wasps. Still other efforts enlist laypeople to tag and analyze images: Eyewire, for example, a game developed by Sebastian Seung ’86, Ph.D. ’90, a professor of computational neuroscience at MIT, involves participants in mapping neurons in the brain."

Howard Rheingold's insight:

Citizen science, enabled by inexpensive but highly accurate sensors and the use of digital media and networks to aggregate and qualify citizen-gathered data, is a form of augmented collective intelligence with a potentially rich future. This Harvard Magazine article is a good contemporary summary. For an in-depth look at this potential, I recommend the book Reinventing Discovery.

The full blossoming of `citizen science` has a long history in the social sciences and humanities that is now becoming much more important thanks to enabling digital technologies. One major example is the ways in which genealogists and academic researchers have collaborated to study demographic change by using sources such as church parish registers to track births, marriages and deaths. The former paper methodology now involves sophisticated digitization, computation and visualization that underpins both academic research and global businesses such as Ancestry. Other examples include public participation in developing museum exhibits and scholarly editions of significant texts.

"Imagine if Twitter were to digest for you the range of agreement, disagreement, and mood of your friends. By pre-digesting information -- self-synthesizing, if you will -- modern maps have been able to foreshadow coming revolutions in information. Unlike the web tools of the early 2000s – chat rooms, forums, wikis, blogs, and podcasts – crowd-sourced maps actually analyze the data given to them, sorting social information into patterns of local, regional, and global patterns. The maps do not merely collect information, as a “memory hole” like Wikileaks does; rather, the maps show the community back to itself, revealing hot-spots of local corruption and pollution, giving activists the tools to target particular places with investigation or protest."

Howard Rheingold's insight:

h/t the indefatigable Michel Bauwens: I don't know whether it can save the commons, but participatory mapping is a particularly useful platform for augmented collective intelligence by all sorts of communities -- from public fruit trees to political protests.

"Levy is currently working on a research program, called IEML (Information Economy Meta Language). IEML is a metalanguage and proposes itself as the language of collective intelligence. As a metalanguage it differs fundamentally from natural languages we know. This can be best understood in the way it is conceived. Natural languages are, in the first place, the results of a process of documenting the spoken word. A metalanguage is artificial and is a result of formalizing ideas, instead of words. The practice of formalizing ideas in a universally adopted metalanguage is well established in the realm of natural sciences. For centuries now, ideas are being documented in terms of formulas, numbers, equations, molecules etc. There is a finite, well structured toolset at the hands of every natural scientist. "

Pierre Levy has been thinking about augmented collective intelligence for a long time. How can the disparate pieces of knowledge contributed by myriad online postings in blogs, question and answer sites, Twitter, etc. be connected in various automatic frameworks? Levy believes a metalanguage (HTML can be seen as a metalanguage) is need.

The scientific revolution in the human sciences will culminate in collective intelligence, a common good which will throttle human development. In a recent book, Levy proposed a “loose IEML model” to monitor the coordination of human development. The axis of human development are defined by “education, health, sustainable economic prosperity, security, human rights, conservation and enrichment of cultural heritage, environmental balance, scientific and technical innovation” which are in accordance with the United Nations Development Program, Levy assures me. I wondered whether a metalanguage which positions itself functionally as neutral (as opposed to Berners Lee universal ontology) should contain assumptions on how western democratic society is structured to which Levy partly agrees that any metalanguage can’t be neutral:

There can be a lot of disagreements about the right ways or methods to improve human development. IEML, as a universal semantic code, can accomodate any method. Above all, IEML provides a common semantic sphere where all disciplines of human sciences can compare their theories and methods and can coordinate their findings at the service of human development. (…) Now, you can say: “Okay, but what if I am against improving health and education because these are western values and / or it has been used to justify western imperialism”. My response is: “It’s up to you!” In general, I do not think that any theory or metalangage can be neutral. Every act, being practical or theoretical, occurs in a hypercomplex context and has an effect on this context. I do not claim any impossible neutrality or objectivity. The objection “you’re not neutral” is besides the point. I have a very precise goal. My aim is to improve human development, collective intelligence and knowledge management in the humanities.

"Stanford computer scientists have created a website to help organizers plan events that are more likely to succeed or allow them to pull the plug on impending flops before they occur.

The website, called Catalyst, is based on a behavioral science concept known as the threshold model of collective action, which posits that people may be reluctant to commit to participating in activity until they see others taking part, at which point interest surges and the activity becomes successful. But if participation doesn’t reach this threshold point, the event is likely to fail.

Catalyst builds this principle into software. The website allows people to enter a few details, such as date, time, description of the event and the number of participants needed to make it a success. If signups don't hit this threshold point by the deadline, Catalyst emails organizers and would-be participants a warning."

Howard Rheingold's insight:

In my 2002 book (12 years ago!) Smart Mobs, I called it "technologies of cooperation" -- working with Institute for the Future, I co-authored a report on Technologies of Cooperation -- and now we're beginning to see computer scientists converge with what social scientists know about collective action to design software that can help people crowdsource.

"The VE wiki continuously monitors and measures how well structured are the groups that collaborate on its pages. If needed, it can also be used to maintain collaborative work within certain levels of equity and evenness. Thus the tool serves a double purpose. On the one hand, it can be used as a monitoring tool, for understanding how collaboration is structured. On the other, it can be employed for adjusting collaboration along particular parameters desired by the instructor or site administrator. The wiki is built around the MediaWiki platform, through which content can be edited by any user, including non-registered ones, all changes are permanently stored, and access to information that was edited or added is instantaneous. In addition, all pages come with “talk” areas, which allow discussions and interactions about the editing process. This makes it well adapted for collaborative work, especially of a textual nature."

Howard Rheingold's insight:

Wiki collaboration is one of the strongest forms of augmented collective intelligence, and as always, the technology requires intelligent use in order for emergent intelligence to manifest in any useful way. This tool enables groups and managers/facilitators of groups to see how contributions are made, who makes the most contributions, and to make these efforts visible to others. Based on research by Sorin Adam Mateir at Purdue, it can be adapted to collaborative learning or to collaborative production.

"We’ve been able to process and make sense of a quarter of a million tweets in the aftermath of Typhoon Yolanda. Using both AIDR (still under development) andTwitris, we were able to collect these tweets in real-time and use automated algorithms to filter for both relevancy and uniqueness. The resulting ~55,000 tweets were then uploaded to MicroMappers (still under development). Digital volunteers from the world over used this humanitarian technology platform totag tweets and now images from the disaster (click image below to enlarge). At one point, volunteers tagged some 1,500 tweets in just 10 minutes. In parallel, we used machine learning classifiers to automatically identify tweets referring to both urgent needs and offers of help. In sum, the response to Typhoon Yolanda is the first to make full use of advanced computing, i.e., both human computing and machine computing to make sense of Big (Crisis) Data"

Howard Rheingold's insight:

Crisis mapping and tools for organizing emergent collective response to disasters is combining human and machine filters to deal with large numbers of responses in the crucial early hours after a crisis -- in this case, Typhoon Yolanda

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